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We study the reduced energy spectrum $\{E_{i}^{(n)}\}$, which is constructed by picking one level from every $n$ levels of the original spectrum $\{E_{i}\}$, in a Gaussian ensemble of random matrix with Dyson index $\beta\in \left( 0,\infty…

Disordered Systems and Neural Networks · Physics 2021-01-19 Wen-Jia Rao , M. N. Chen

Random matrix theory has proven very successful in the understanding of the spectra of chaotic systems. Depending on symmetry with respect to time reversal and the presence or absence of a spin 1/2 there are three ensembles, the Gaussian…

Mesoscale and Nanoscale Physics · Physics 2022-01-19 M. Richter , A. Rehemanjiang , U. Kuhl , H. -J. Stöckmann

We propose a theoretical framework to study the eigenvalue spectra of the controllability Gramian of systems with random state matrices, such as networked systems with a random graph structure. Using random matrix theory, we provide…

Systems and Control · Computer Science 2016-09-16 Victor M. Preciado , M. Amin Rahimian

We propose a dynamical process for network evolution, aiming at explaining the emergence of the small world phenomenon, i.e., the statistical observation that any pair of individuals are linked by a short chain of acquaintances computable…

Data Structures and Algorithms · Computer Science 2008-03-04 Augustin Chaintreau , Pierre Fraigniaud , Emmanuelle Lebhar

We study the universality of spectral statistics of large random matrices. We consider $N\times N$ symmetric, hermitian or quaternion self-dual random matrices with independent, identically distributed entries (Wigner matrices) where the…

Mathematical Physics · Physics 2015-05-18 Laszlo Erdos

In this thesis, we extend the recently introduced theory of stochastic modified equations (SMEs) for stochastic gradient optimization algorithms. In Ch. 3 we study time-inhomogeneous SDEs driven by Brownian motion. For certain SDEs we prove…

Probability · Mathematics 2025-11-26 Stefan Perko

In classical systems, our recent theoretical study provides new insight into how spatial constraint on the system connects with macroscopic properties, which lead to universal representation of equilibrium macroscopic physical property and…

Disordered Systems and Neural Networks · Physics 2016-11-10 Koretaka Yuge , Kazuhito Takeuchi , Tetuya Kishimoto

We show that renormalization group (RG) theory applied to complex networks are useful to classify network topologies into universality classes in the space of configurations. The RG flow readily identifies a small-world/fractal transition…

Disordered Systems and Neural Networks · Physics 2010-01-30 Hernán D. Rozenfeld , Chaoming Song , Hernán A. Makse

A known result in random matrix theory states the following: Given a random Wigner matrix $X$ which belongs to the Gaussian Orthogonal Ensemble (GOE), then such matrix $X$ has an invariant distribution under orthogonal conjugations. The…

Probability · Mathematics 2019-10-02 Jose Angel Sanchez Gomez , Victor Amaya Carvajal

The Random Geometric Graph (RGG) is a random graph model for network data with an underlying spatial representation. Geometry endows RGGs with a rich dependence structure and often leads to desirable properties of real-world networks such…

Social and Information Networks · Computer Science 2022-08-25 Quentin Duchemin , Yohann de Castro

Quantum chaotic systems with one-dimensional spectra follow spectral correlations of orthogonal (OE), unitary (UE), or symplectic ensembles (SE) of random matrices depending on their invariance under time reversal and rotation. In this…

Quantum Physics · Physics 2024-01-09 Jisha C , Ravi Prakash

Several spectral fluctuation measures of random matrix theory (RMT) have been applied in the study of spectral properties of networks. However, the calculation of those statistics requires performing an unfolding procedure, which may not be…

Disordered Systems and Neural Networks · Physics 2019-11-14 G. Torres-Vargas , R. Fossion , J. A. Méndez-Bermúdez

Nonextensive aspects of the degree distribution in Watts-Strogatz (WS) small-world networks, $P_{SW}(k)$, have been discussed in terms of a generalized Gaussian (referred to as {\it $Q$-Gaussian}) which is derived by the three approaches:…

Disordered Systems and Neural Networks · Physics 2009-11-11 Hideo Hasegawa

A new class of Random Matrix Ensembles is introduced. The Gaussian orthogonal, unitary, and symplectic ensembles GOE, GUE, and GSE, of random matrices are analogous to the classical Gibbs ensemble governed by Boltzmann's distribution in the…

Statistical Mechanics · Physics 2019-07-03 Maciej M. Duras

Fractional-order dynamical networks are increasingly being used to model and describe processes demonstrating long-term memory or complex interlaced dependencies amongst the spatial and temporal components of a wide variety of dynamical…

Optimization and Control · Mathematics 2021-08-04 Sarthak Chatterjee , Andrea Alessandretti , A. Pedro Aguiar , Sérgio Pequito

Bayesian networks model relationships between random variables under uncertainty and can be used to predict the likelihood of events and outcomes while incorporating observed evidence. From an eXplainable AI (XAI) perspective, such models…

Machine Learning · Computer Science 2024-02-20 Damy M. F. Ha , Tanja Alderliesten , Peter A. N. Bosman

The spectral form factor of random matrix theory plays a key role in the description of disordered and chaotic quantum systems. While its moments are known to be approximately Gaussian, corrections subleading in the matrix dimension, $D$,…

Quantum Physics · Physics 2026-01-06 Alex Altland , Francisco Divi , Tobias Micklitz , Silvia Pappalardi , Maedeh Rezaei

Recently, Aizenman and Warzel discovered a mechanism for the appearance of absolutely continuous spectrum for random Schroedinger operators on the Bethe lattice through rare resonances (resonant delocalization). We extend their analysis to…

Mathematical Physics · Physics 2015-06-15 Mira Shamis

A Random Geometric Graph (RGG) ensemble is defined by the disordered distribution of its node locations. We investigate how this randomness drives sample-to-sample fluctuations in the dynamical properties of these graphs. We study the…

Physics and Society · Physics 2018-12-05 Matthew Garrod , Nick S. Jones

In this article the statistical properties of symmetrical random matrices whose elements are drawn from a q-parametrized non-extensive statistics power-law distribution are investigated. In the limit as q->1 the well known Gaussian…

Statistical Mechanics · Physics 2007-05-23 John Evans , Fredrick Michael